This project links two broadly important problems in biomedical science. First, the human immunodeficiency virus (HIV) infects 5 million people annually and causes ~3 million deaths through AIDS. Studies of the structural biology of HIV have contributed significantly to therapeutic drug strategies against the virus. The HIV RNA genome is directly involved in almost every aspect of the retroviral infectivity cycle, but remains the least well understood component of HIV. A comprehensive structural map of the HIV-1 genome will make it easier to identify new targets for antiretroviral drugs and to design siRNA and other antisense approaches. Second, essentially all RNAs function in biology only after they fold into a specific secondary structure. Existing RNA structure mapping technologies are laborious and error prone and yield an incomplete view of RNA structure. Our laboratory has developed a new RNA structure analysis technology that solves the problems associated with traditional approaches and that is supported by extensive successful exploratory work. We will develop RNA structure analysis into a mature technology roughly as straightforward as DNA sequencing is today. We seek to use this technology to analyze the structure of an entire HIV-1 RNA genome. In collaboration with experts in HIV biology and in bioinformatics, we will tackle the following Aims: (1) Create a complete, seamless technology for quantitative analysis of the structure of long RNAs. We will make this technology accessible to all interested biomedical scientists. (2) Use our high throughput RNA structure mapping technology to obtain quantitative structural information for an entire HIV-1 RNA genome. (3) Determine differences in the genomic RNA structure at different stages in the viral life cycle. This work is likely to advance significantly our understanding of how the human immunodeficiency virus works and thus how to interfere with HIV functioning. This work accomplishes this goal by creating a tool -- facile RNA structure analysis - that can be broadly used by biomedical scientists to address diverse biological problems with consequences for human health. [unreadable] [unreadable]